AI & Machine Learning | Regrid Land Parcel Data

Better data input for property intelligence

AI and machine learning models need clean, consistent property context. When parcel records vary across counties, teams spend more time normalizing data and less time building useful models. With Regrid’s standardized nationwide parcel layer, you can:

100%

U.S. Parcel
data coverage

Start from a consistent property reference

Connect imagery, risk layers, internal records, and model outputs to parcel IDs.

Evaluate completeness before modeling

Understand field availability, coverage, and refresh context before building or retraining models.

Move from prediction to location intelligence

Turn model outputs into parcel-based insights that can be mapped, shared, and used in products.

Climate risk modeling at scale

A mortgage technology provider used Regrid parcel data and Parquet cloud processing to support climate risk models. The updated pipeline reduced upfront engineering work and lowered ongoing maintenance costs.

Austin growth analysis with Makepath

Makepath combined machine learning tools, Planet imagery, and Regrid parcel data to study growth across Austin. The work produced change detection maps across 6,750 square miles from 2017 to 2022.

Land use classification from imagery

Regrid worked with a partner using computer vision on aerial imagery to improve land use analysis. Parcel data helped inform and ground-truth land use codes for better LBCS coverage, accuracy, and currency.

Parcel boundaries and sizes, owner names and mailing addresses, buildings, known addresses, zoning, valuation, and other parcel attributes delivered in one consistent structure.
100% U.S. parcel coverage, with refresh dates and attribute completeness that help teams understand data readiness before modeling, analysis, or deployment.
Use bulk files and cloud delivery for modeling and analytics, or API, tiles, and Feature Service for applications, dashboards, and map-based products.

Yes. Regrid provides standardized parcel attributes and consistent identifiers that help teams build reusable features across counties and markets. Teams can also review attribute completeness before modeling.
Regrid supports bulk delivery, including Parquet and cloud delivery, so data science teams can process parcel data in modern analytics environments.
Yes. Regrid supports API, tiles, and Feature Service delivery for apps, dashboards, and portals. Licensing details depend on how the data is displayed, shared, and protected from raw geometry extraction.
Regrid refreshes counties on an ongoing schedule and publishes coverage, refresh dates, and attribute completeness so teams can understand what data is available and how recently it was updated.
Most teams start with one delivery method, connect it to existing workflows, then expand to additional access methods as needs grow across phases and business units.

Premium Parcels

Spatial Add-Ons

Roadway ROW

Data Access

Support

Content

Programs

Shop

Premium Parcels

Roadway ROW

Spatial Add-Ons

Data Access

Support

Programs

Content

Shop

INDUSTRIES

Nationwide parcel data for AI and machine learning

Regrid gives teams leveraging AI and machine learning standardized parcels, ownership, addresses, buildings, zoning, and valuation data for better models and property intelligence.

Better data input for property intelligence

Start from a consistent property reference

Evaluate completeness before modeling

Move from prediction to location intelligence

Built for core AI and machine learning workflows

See how standardized parcel data supports modeling, imagery analysis, and property intelligence at scale.

Build better training datasets

Ground imagery analysis in parcels

Model property risk and context

You're in great company

Real examples from AI and machine learning projects

Regrid supports data science, engineering, and product teams that need standardized parcel data for modeling, prediction, imagery analysis, and property intelligence at scale

Climate risk modeling at scale

Austin growth analysis with Makepath

Land use classification from imagery

Explore the coverage map

What you get

Critical attributes, standardized

Nationwide coverage, kept current

Delivery that fits data science teams

Talk to an AI and machine learning parcel data expert

Frequently asked questions

Can Regrid data support training and feature engineering?

How does Regrid support cloud and bulk data workflows?

Can we display parcel data and model outputs in our product?

How current is Regrid parcel data?

What does implementation look like for enterprise teams?

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